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Parallel history matching and associated forecast at the center for interactive smart oilfield technologies

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Abstract

We have developed a parallel and distributed computing framework to solve an inverse problem, which involves massive data sets and is of great importance to petroleum industry. A Monte Carlo method, combined with proxies to avoid excessive data processing, is employed to identify reservoir simulation models that best match the oilfield production history. Subsequently, the selected models are used to forecast future productions with uncertainty estimates. The parallelization framework combines: (1) message passing for tightly coupled intra-simulation decomposition; and (2) scheduler/Grid remote procedure calls for model parameter sweeps. A preliminary numerical test has included 3,159 simulations on a 256-processor Intel Xeon cluster at the USC-CACS. The results provide uncertainty estimates of unprecedented precision.

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References

  1. Landa JL, Guyaguler B (2003) A methodology for history matching and the assessment of uncertainties associated with flow prediction, SPE 84465. Society of Petroleum Engineers, Richardson

  2. Mosegaard K, Tarantola A (2002) Probabilistic approach to inverse problems. In: International handbook of earthquake and engineering seismology, Part A. Academic Press, p 237

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  4. We have used the AlphaServer at the Pittsburgh Supercomputing Center

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Authors and Affiliations

  1. Collaboratory for Advanced Computing and Simulations (CACS), Center for Interactive Smart Oilfield Technologies (CiSoft), University of Southern California, Los Angeles, CA, 90089-0242, USA

    Ken-Ichi Nomura

  2. Department of Computer Science, University of Southern California, Los Angeles, CA, 90089-0242, USA

    Rajiv K. Kalia

  3. Department of Physics and Astronomy, University of Southern California, Los Angeles, CA, 90089-0242, USA

    Aiichiro Nakano

  4. Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA, 90089-0242, USA

    Priya Vashishta

  5. ChevronTexaco, 6001 Bollinger Canyon, San Ramon, CA, 94583, USA

    Jorge L. Landa

Authors
  1. Ken-Ichi Nomura
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  2. Rajiv K. Kalia
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  3. Aiichiro Nakano
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  4. Priya Vashishta
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  5. Jorge L. Landa
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Correspondence to Ken-Ichi Nomura.

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Nomura, KI., Kalia, R.K., Nakano, A. et al. Parallel history matching and associated forecast at the center for interactive smart oilfield technologies. J Supercomput 41, 109–117 (2007). https://doi.org/10.1007/s11227-006-0031-2

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  • DOI: https://doi.org/10.1007/s11227-006-0031-2

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